Data Stream Mining Techniques

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• HASAN BULUT

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• AYTUĞ ONAN

This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographi…

Ensemble learning combines a series of base classifiers and the final result is assigned to the corresponding class by using a majority voting mechanism. However, the base classifiers in the ensemble cannot perform equally well. Therefore, the base classifiers should be assigned different weights in order to increase…

Machine learning techniques will contribution towards making Internet of Things (IoT) symmetric applications among the most significant sources of new data in the future. In this context, network systems are endowed with the capacity to access varieties of experimental symmetric data across a plethora of network devic…

• HALİT YAHYA

Machine learning techniques will contribution towards making Internet of Things (IoT) symmetric applications among the most significant sources of new data in the future. In this context, network systems are endowed with the capacity to access varieties of experimental symmetric data across a plethora of network devic…

• SHEHZAD ASHRAF

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• ADİL BAYKASOĞLU

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• AHMET MURAT ÖZBAYOĞLU

Cloud computing is the latest emerging trend in distributed computing, where shared resources are provided to end-users in an on demand fashion that brings many advantjuages, including data ubiquity, flexibility of access, high availability of resources, and flexibility. The task scheduling problem in Cloud computing…

• NIMA JAFARI NAVIMIPOUR

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• AYŞE MERVE ACILAR

The problem of statistics and aggregate maintenance over data streams has gained popularity in recent years especially in telecommunications network monitoring, trend-related analysis, Web-click streams, stock tickers, and other time-variant data. The amount of data generated in such applications can become too large…

When collecting subjective human ratings of items, it can be difficult to measure and enforce data quality due to task subjectivity and lack of insight into how judges’ arrive at each rating decision. To address this, we propose requiring judges to provide a specific type of rationale underlying each rating decision.…